AntiMPmod: Prediction of Antimicrobial Potential of a Chemically Modified Peptide From Its Tertiary Structure

Welcome to the official repository for AntiMPmod, a computational method and web server for predicting the antimicrobial potential of chemically modified peptides from their tertiary structures. This resource is designed to support researchers in peptide therapeutics, antimicrobial drug discovery, and computational chemistry. Web Server: http://webs.iiitd.edu.in/raghava/antimpmod/ Structure Prediction Server (PEPstrMOD): http://webs.iiitd.edu.in/raghava/pepstrmod/ Standalone (Docker): Pull image raghavagps/gpsraghava and run PERL code from the gpsr folder Citation Agrawal, P., & Raghava, G. P. S. (2018). Prediction of Antimicrobial Potential of a Chemically Modified Peptide From Its Tertiary Structure. Frontiers in Microbiology, 9:2551. https://doi.org/10.3389/fmicb.2018.02551 About the Tool AntiMPmod is the first method developed specifically to predict the antimicrobial activity of chemically modified peptides using their 3D tertiary structures. Unlike all previous AMP prediction methods that rely solely on natural amino acid sequences, AntiMPmod leverages structural features extracted via SMILES format — including atom composition, diatom composition, molecular fingerprints, 2D chemical descriptors, and binary profiles — to handle the full diversity of chemical modifications. The tool integrates data from: SATPDB — Structurally Annotated Therapeutic Peptide Database (source of modified AMPs and non-AMPs) PEPstrMOD — for tertiary structure prediction of modified peptides up to 25 residues OpenBabel — for SMILES format conversion from PDB structures PaDEL — for computing molecular descriptors and fingerprints